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 "cells": [
  {
   "source": [
    "# 直观理解高斯核函数"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(-4, 5, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "array([-4, -3, -2, -1,  0,  1,  2,  3,  4])"
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = np.array((x >= -2) & (x <= 2), dtype='int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "array([0, 0, 1, 1, 1, 1, 1, 0, 0])"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.scatter(x[y==0], [0]*len(x[y==0]))\n",
    "plt.scatter(x[y==1], [0]*len(x[y==1]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gaussian(x ,l):\n",
    "    gamma = 1.0\n",
    "    return np.exp(-gamma * (x-l)**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "l1, l2 = -1, 1\n",
    "\n",
    "X_new = np.empty((len(x), 2))\n",
    "for i, data in enumerate(x):\n",
    "    X_new[i, 0]= gaussian(data, l1)\n",
    "    X_new[i, 1]= gaussian(data, l2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.scatter(X_new[y==0,0], X_new[y==0,1])\n",
    "plt.scatter(X_new[y==1,0], X_new[y==1,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}